Itamar Rogel

How to analyze mobile user behavior

As mobile applications exponentially grow, with over 3.5 million of them on the Google Play store and over 2 million on the Apple App store, so does the need to better understand user behavior.

In order to better understand user engagements and to correctly track user behavior, companies must use analytics tools to comprehend their customer interactions.

Getting to know your users through analyzing the way they operate applications becomes a challenge when addressing millions of actions. When aiming to analyze such user experience and user behavior, a business must take into account that they are multi-faceted, constantly changing, and ever-more challenging.

How to analyze mobile user behavior

Developers must now employ a combination of user quantitative and qualitative data points, to figure out both the “what they want” with “why they want it”. As app features are more accessible than ever, customer interactions call for tracking and analysis, which would yield insights companies can use for improvements and upgrades.


And mobile analytics is all about that: Tracking real-time millions of data points, both quantitative and qualitative, and analyzing them in order to increase user retention and engagement.


Mobile application user behavior requires direct tracking analytics but also monitoring and analyzing user feedback across many digital open web points. User discussions and conversations about all related-application data features, once collected and dissected, can lead a studio to make actionable app insights.

Take, for example, unresponsive gestures, namely an app situation where customers tap a button but are met with absolutely no response from the app. There is the technology side that calls for fixing the problem, but there are also the online responses from players, which call for a user data analysis.


Take for example a user’s bug event, which happens all the time. Developers must deal with the mobile app technological challenges, but they can also learn a lot from analyzing their customer feedback data, as it is very telling about user behavior and user interactions.



Once both data funnels are analyzed together, a full mobile app user behavior picture can form.


Developers then gain opportunities to identify user challenges and optimize their mobile apps and features.

On the tech side, developers hold various session recordings, following customers as they operate an app.

They employ touch heatmaps, the tool that collects users’ gestures data, as a user interacts with the app. Such mobile engagement app data tell companies a lot regarding user behavior.

But the additional side of tracking and analyzing user behavior from their real-time online mentions, as they appear in such places such as app review boards, social media, and forums, can add lots of invaluable data on how users interact and about their thoughts on the product.

As the mobile world is getting more competitive, and as mobile apps are constantly vying for users’ attention, data analytics tools become more important and can sometimes mean the difference between success and failure.

User retention can become more difficult since players have many different mobile applications, free and paid, from which to choose. So analytics, quick fixes, and app improvements become critical.

But app data collected from touch heatmaps and session recordings may not be sufficient. Companies need to understand what their customers feel and think about their products, so user online comments serve as the necessary data to complement the tech side of things.

Developers can then optimize their product-building process. To understand your users and optimize your app, employ all users’ mobile app data and insights tools. User behavior complexities can be made easier to figure out once all data pieces are taken together.

Metrics parameters and feedback content viewpoints can be analyzed and evaluated together for a clearer and more precise picture. Users’ analytics does not have to remain a mystery should all data points be considered for progress.

When it comes to developing an app or any digital platform tool, there are a few paths and mobile issues to consider.


General product development considerations



  • An application design’s complexity


Just how complex must your application be?


As mobile developers try to track user-product engagement and the way users interact with the features they have built, there comes to mind the sophistication dilemma. If we create an application too difficult, many users would feel inept. But if we make it too light and easy, it may turn away hardcore customers.


The customer targeting funnels present an issue to both marketers and developers. There are usability factors to determine which begs the question of just how accessible the application is going to be.

Opening it for a wider audience funnel may mean more revenues for businesses, but if the app is too simple, users may give up on it quickly and move to some other app. In the event that the screen app is too demanding, that may hurt the marketing funnel, reduce conversion, and would lead to less revenue.


The design issues and tools meet the user capabilities factors. And the design aspects are wide-ranging, as they pertain to visuals, motor gestures, and cognitive capabilities to consider.


There are also short and long-term mobile app development ramifications. Do we make the first stages fairly easy and increase complexity as the app moves forward? Do we offer future updates which are harder or easier to employ?


On yet another front, there is the issue of clarity. Are the mobile app features clear enough to understand and operate? Does a user know how to get from point A to point B? And if users get confused, do they know how to find a quick help tool (a min read manual or instructions) and employ it?


  • Your user capabilities

The second consideration to make continues the first point.

It is sometimes necessary to perform cohort analysis, by which categorization of users into groups with common characteristics is performed.

So after defining your audience, every developer must consider that there will be cohort variations within this user-targeted group. So although there will be many shared characteristics among a specific group of consumers, there still would also be some differences to be taken into development consideration.


There will be customers who are quicker to figure out a new mobile app feature while other early adopters would react slower to new rules and challenges. The latter may need more onboarding tools. So a need to balance the actions and several other usability issues in the development process, based on the cohort’s analytics, must be taken into account.

Another example of a user’s engagement and capability is the issue of interruptions.

As in life, consumers often take breaks from tapping their screens, so developers must make flexible session lengths and accommodate task-switching and distracting factors. There are mobile app studios that offer pop-ups with short explanations of changes made while the user was away. Or they offer reminders or unique daily tasks to smooth the return process of users to the mobile screen.


Here too developers must identify the technology required and show flexibility. They could offer certain more advanced players the option to hide or delete those pop-ups, so as not to interrupt their engagement flow. However, other customers may need the assistance of such pop-ups, so the proper arrangements must be made for them.

Video and audio screen adjustments, another aspect to be considered, must also be developed with flexibility parameters in mind. As data analysis of gestures, interactions, and conventions of usage takes place, and cohorts analytics is employed for a variety of user groups, a custom plan must be built to accommodate and personalize as much as possible every mobile app for its users.


The ways users interact with your app, and as more data to track user behavior is piling up, users show developers how they should proceed with the games developed for mobile apps.


  • Leveraging familiarity (“give me the same, only different”)

There’s no real onboarding for many customers testing new mobile app choices on their small screens. A lot of them come to the app they just downloaded with knowledge of standard features and logical application truth.

So their expectation is to ease into a new mobile application fairly quickly, basing their confidence on acceptable industry guidelines such as progression structures and known app paths.

So it is up to developers to plan new and exciting mobile apps, similar in structure and general rules but fresh in their design and story angles. The mantra of “give me the same, only different” known in the entertainment world of movies and television programs, applies here too.

Originality is always welcomed in the app world, but the ability to leverage previous applications’ familiarity is supposed to make users interact more freely and easily with new apps.

Consistency within the app itself is also important.

While challenges can change and actions may vary as the mobile app usage progresses, consumers still expect a certain level of familiarity, clarity, and a similar overall structure. User behavior for the consistent screen features should be measured and matched against the “surprise elements”, if they exist, in every app choice.


  • Maintaining some diversity and flexibility (to appeal to a wider audience)

User retention and customer satisfaction, always on the minds of app developers, must use analytics tools (app analytics) to determine if the companies’ marketing and business funnels’ expectations materialize for the applications they promote.

Thus the constant discussion of just how wide an appeal should an app have, and how certain features can help the conversion process of more users.

So whatever the genre is, developers must keep their apps as flexible and as diverse when it comes to iconography and terminology usage. Increasing app screen time and retention can come from keeping an app game distinct and focused, yet appealing to as wide an audience as possible.


  • Tutorials and help guides

Play, trial, and error is the approach many users take when beginning to test new app games.


But depending on the user level of expertise, other mobile app participants still need onboarding assistance. Users can choose to go over tutorials and help guides, and it is the developers’ responsibility to provide them with as much clarity as possible.

Once the effort to track user behavior results in figuring out what kind of help customers are looking for, a line must be drawn to balance between flooding the screen with pop-ups and not giving any help at all. Developers usually offer help so that every customer can decide for himself just how much tutoring he needs for using a specific feature.

Decisions on how to offer help, at what points in the app, and how often, all figure out in the platform development process. Tracking user experience many times would give directions on that matter.


Help is definitely required in trying to get users out of errors. Once the behavior of unresponsive gestures is analyzed, and cohort analytics is employed, developers can figure out the best technical and logical ways of offering mobile app help.


So it is the double responsibility of app developers to first minimize as much as possible the appearance of errors, and second, should errors appear, offer the right help to consumers.


  • Combining and balancing the above factors

Building and developing a successful mobile app is never an easy task since too many considerations need to be made by developers. Technology, business, psychology, and customers’ behavior data are among the factors to include in new app development.


In order to increase conversions and user retention, or simply guarantee a successful engagement of a user with a mobile application, all of the above mentioned items must be carefully balanced. Customer conversion and then retention is built on the delicate combination of those different elements.

The paths to increase the chances of success go through the metrics analysis as well as the quantitative analytics of what customers comment and mention all over the open web.



Measuring quantitative performance factors



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  • Financial measures: units sold, apps downloaded, in-app purchases, average revenue per user, lifetime value

As mobile app businesses weigh down their revenues and profits, a variety of metrics make up their calculations regarding the profitability of a mobile application.


The amount of units sold, or in this app world the number of downloads, is the first business consideration. Then there are upsells from in-app purchases of extended features.

Businesses also measure how their marketing efforts have fared by looking into the average revenue per user, a calculation that takes into account both his initial purchase of an application and then any additional money he invested in adding up more mobile features to his pool.

Trying to track user behavior in a mobile app also runs through the measurement of the lifetime value of a user. In other words, how much money the app made out of every single player for the entirety of his life cycle of playing a specific game.

App analytics tools also show how the marketing team performed, by reaching the maximum conversion possible out of all funnel efforts trying to target new consumers. Website activities, social media paid and organic content and public relations actions can all be measured for their return on investment.


  • Usability measurements: gaming stickiness

Other than monetary measurements, mobile app developers check how customers and users stick to their screen apps and games. The length of time a customer sticks to his screen for gaming sessions can tell a lot about his engagement and enjoyment of the product.


Studios also employ Localytics, which is a specific software dedicated to tracking millions of data points from mobile app features. Localytics is used to measure user flows and funnel performances.

Using Localytics to measure play events across a variety of features helps developers identify paths, funnels and patterns from multitudes of screens.

For application stickiness and in order to track user behavior even further, tools such as heat maps are used to collect data from session recordings on how users interact with mobile apps. Touch heatmaps evaluate gestures such as taps, swipes, pinches and more, in the effort to learn how users interact with their screens.

Stickiness, whether in a free or paid mobile app, can then be further evaluated for specific gestures and actions from users. Tracking user behavior to understand how customers approach their screen features and paths, enables developers to learn what works and what needs improvement. For that, technology tools and analytics such as touch heatmaps in session recordings are applied.

The user behavior analysis from a platform session recordings and touch heatmaps can also tell developers what works in terms of planning of future mobile applications.

It is also worth mentioning that many analysts turn to google analytics for an evaluation of mobile app usage. Google follows paid ads performance and conversions through its Google analytics platform.

There are also various google analytics measurements of user engagement and screen interactions.


Just how popular are mobile apps?


Digging deeper into mobile applications’ user behavior becomes even more critical due to their immense popularity and the tough market competition among them.

Mobile application developers do the best that they can to understand and analyze users’ and customers’ behavior so that they can increase, or at least maintain, their share of the huge revenues pie.


Statistics such as in the 6 insights to guide your mobile & app analytics strategy reveal that 80% of all web users deal with 5 applications on average or a regular basis, out of a larger total of 28 applications they have downloaded to their mobile phones.

Another statistical figure of note is that the applications’ uninstallation rate can reach 54%. That is explained by users giving up on applications and uninstalling them due to technical problems and page crashes.


So there is no medium point: Applications must be built properly and as bug-free as possible, otherwise users lose interest quickly and uninstall them. Since there are so many alternative options, players do not show patience for applications having problem technology events that are not resolved quickly.


Measuring qualitative performance factors


There are several factors that make up the list of customer feedback elements that developers must measure for the broader application performance picture.


  • Overall brand sentiment

Positive mentions over negative comments from users all over the open web, when tracked during a specific time period, resulting in the application brand sentiments score tool.


  • Features feedback

Users’ reactions all over the open web regarding an application’s features, whether design-related or story-wise, can tell developers what works and what requires upgrades and improvements.


  • Technical items

To analyze bug events or technology-related failures, developers using AI-powered platforms can track problems quickly and act to fix them for a smooth-operating application.


  • Customer service ratings

Many customers view business customer service operations as just as important as they view the application itself. A complaint email to the business website or negative comment in a forum can tell developers what customers want to see improved.



Affogata: the “Why” behind the “What”


Affogata offers businesses a customer feedback and a consumer’s voice analysis platform.

Businesses wishing to dig deeper into their users’ needs and wants, as they try to increase revenues, conversion, and retention to their screen applications, can better understand their customer voice by analytics tools from countless comments and conversation funnels tracked from all over the open web.


The path to understanding a customer is by both measuring his user behavior, through session recordings, screen touch heatmaps, and cohort evaluation, as well as dissecting his conversations about his application usage experience.


These two paths would help developers better track user behavior.